I’m going to cut down the TUNA example greatly, to blog-post size. What we are going to be simulating is sticky objects in a pipeline, for example sticky blood platelets moving through a blood vessel. Our platelets will be represented as data that is passed between active “site” processes; our blood vessel will be a one-dimensional pipeline of site processes. Each process will be connected to its neighbours with a channel that can pass platelets. All the processes will be enrolled on the tick barrier, as is customary in CHP simulations.

We’ll begin the code with a helper function (one that I would like to see in the standard library) that iterates forever with a state value being passed through, and our platelet data type:

The pipeline generates platelets regularly, one every three time-steps (this is coded as the simple on-off-off sequence). When it is performing an “on” time-step, it generates a platelet with a random shade, then uses behaviours to offer to once send the platelet until tick happens (i.e. the frame is over). The next site in the pipeline may not take the new platelet if the site is full and not moving this time-step, so the platelet may get discarded in that case. In the off state, the generator waits for the tick to end the frame, but also offers to tell the site ahead of it that the generator is empty (signified by sending Nothing rather than Just a platelet).

The main logic is in the site process, which also has two states, empty and full:

Each time, if there is Just a platelet returned by the function, the next state will be full, otherwise it will be empty. The initial state is empty (the Nothing value). The empty state consists of three possible behaviours:

In an empty state, a site will read in a new platelet from the previous site in the pipeline (if available), it will offer to communicate to the next site in the pipeline that it is empty, and it will finish this behaviour when the tick event happens. The value returned is the result of reading from the channel, which will be Nothing if no read occurred or if we read in a Nothing value (and hence the site remains empty) or Just the result of the read if it did happen and was a platelet (in which case the site will become full). It is possible to reduce the amount of communications happening with empty processes, but I want to keep this example simple if I can.

We will pick this code apart, bit by bit. It is primarily an offer between the tick to end the frame and another behaviour, called probablyMove. When the site is full, it has a 5% chance of refusing to do anything, meaning that a single platelet will not move in 5% of time-steps. So it starts by generating a random number between 0 and 1. If this is under 0.05 (i.e. a 5% chance), the probablyMove behaviour is stop, meaning it will not move — the site will just wait for the end of the frame in these 5% of cases.

In the other 95% of the time-steps, a move is offered, using conjunction. The site offers to read a value from the previous channel (which may be Just a platelet, or a Nothing value signifying the site was empty) and send on its current platelet, shuffling the platelets along the pipeline. So its overall behaviour is that it will send on its current platelet, if and only if: the previous site is empty, or the previous site is full and willing to send its platelet on (it won’t be willing 5% of the time). So a platelet can only move if there is no-one behind it, or if the platelet behind it moves too.

The implications of this behaviour are that once platelets are in adjoining cells, they only move on together. Thus any platelets that bump together form a notional clot that stays together forever after. This clot is not explicitly programmed and has no representation in the program. It is emergent behaviour that arises out of the local rules of the site process; each site only communicates with the site either side of it, and yet the program logic means that clots that are tens of platelets long could form, and would be unbreakable.

The other neat thing that arises out of the logic comes from the 5% chance. In 5% of time-steps a platelet will not move. (This is what allows the platelets to bump together in the first place.) Since a clot can only move when all its platelets move, a two-platelet clot has a roughly 10% chance of not moving (really: 1 – 0.95^2), and a three-platelet clot has about a 14% chance of not moving (1 – 0.95^3). So big clots will move slower, which means that the platelets behind become more likely to join on. Despite only having a local probability of not moving, we get the behaviour that larger clots are less likely to be able to move.

Enough on the site process; at the end of the pipeline is a platelet printer, that swallows up any platelets and prints out how large each clot was that reached the end of the pipeline:

That is terribly unexciting, so I’m going to give a sneak video preview of a visualisation that I will go through in my next post. The 1D pipeline of sites is visualised left-to-right, with each tall bar being a platelet (or black for empty). When the bar flashes white, this is in the 5% of cases where the platelet is refusing to move. Hence you can see that when the larger clots form, the white flashes of the various platelets prevent the clot from moving: